Providers to have access to new model privacy notices

New descriptions will better explain how, why health information is shared, says Genevieve Morris.


The Office of the National Coordinator for Health Information Technology has selected three winners of a challenge the agency issued in December.

Software developers, data privacy experts and other stakeholders submitted entries intended to update the model privacy notice to be more applicable for use in a mobile health environment.



Mobile applications and wearable devices that collect data have changed the health IT market, according to ONC, which called for innovators to create an online tool generating a user-friendly snapshot of a product’s privacy practices. The goal was to produce a customizable model privacy notice for health IT developers that makes the notice more easy for consumers to understand.

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“Compared to when the original model privacy notice was released in 2011, the consumer-facing health IT market now features a much larger variety of digital health technologies that collect information,” says Genevieve Morris, principal deputy national coordinator for health IT. The winning tools, she adds, will help consumers know how and why their health information will be shared.

The model privacy notice is a voluntary resource and is similar to the FDA Nutrition Facts Label in helping consumers make informed choices when selecting products. ONC started the privacy notice initiative in March 2016 by issuing a request for information and getting insights from developers, providers and consumer organizations. The three winners are:

1. R. Jason Cronk and Professor Daniel Solove’s generator features a side-by-side, live-updating view allowing application developers to see the Model Privacy Notice (MPN) as they complete the app’s sections. It also clearly shows the developer which sections are completed or require more information. The MPN most successfully combines the clarity and simplicity of a nutrition facts-type label with visual icons that aid comprehension of the privacy concepts. The first-place team, which was awarded $20,000, best specified which terms and language were changed to enhance consumer understanding.

(https://github.com/privacymaverick/mpn-generator)

2. 1upHealth’s team uses a side-by-side view that includes live checking of entered information to verify websites and phone number formats. The generated MPN allows for extensive customization, available in HTML, JSON, and Markdown formats. Detailed interviews and usability testing were held to receive consumer feedback. The second-place team was awarded $10,000.

(https://github.com/rickysahu/mpngen)

3. MadeClear.io’s generator features expandable headers allowing developers to easily see how far they have progressed in completing the MPN. The MPN uses alternating background images that help differentiate the sections and colorful icons that add context to the privacy language. The team’s consumer testing included surveys completed by 30 individuals. The third-place submission was awarded $5,000.

(https://github.com/ajveach/MadeClear)

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